Surrogate Modeling of Ultrasonic Testing Simulations Using Variable-Fidelity Models and Data-Driven Methods
Date
Authors
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Research Projects
Organizational Units
Journal Issue
Is Version Of
Versions
Series
Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.
This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.
Department
Abstract
Ultrasonic testing (UT) is used to detect internal flaws in materials or to characterize material properties [1]. Computational simulations are an important part of the UT process. Having fast surrogate models for ultrasonic testing (UT) simulations is key for inverse analysis and model-assisted probability of detection (MAPOD) in the field of nondestructive evaluation. In fact, it is impractical to perform the aforementioned tasks in a timely manner using current simulation models directly. Fast surrogate models can make these processes computationally tractable. This paper presents investigations of using surrogate modeling techniques to create fast approximate models of UT simulator responses. In particular, we propose to integrate data-driven methods (here, kriging interpolation [2]) with variable-fidelity models [3] to construct an accurate and fast surrogate model. These techniques are investigated using test cases, shown in Fig. 1, involving UT simulations of metal components immersed in a water bath during the inspection process. We will apply the full ultrasonic solver and the surrogate model to the detection and characterization of the flaw. The methods will be compared in terms of quality of the responses and the computational time.